Experimental demonstration of a skyrmion-enhanced strain-mediated physical reservoir computing system.

Sun, Yiming; Lin, Tao; Lei, Na; Chen, Xing; Kang, Wang; Zhao, Zhiyuan; Wei, Dahai; Chen, Chao et al. · Nat Commun · 2023

basic_science · Level V

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Abstract

Physical reservoirs holding intrinsic nonlinearity, high dimensionality, and memory effects have attracted considerable interest regarding solving complex tasks efficiently. Particularly, spintronic and strain-mediated electronic physical reservoirs are appealing due to their high speed, multi-parameter fusion and low power consumption. Here, we experimentally realize a skyrmion-enhanced strain-mediated physical reservoir in a multiferroic heterostructure of Pt/Co/Gd multilayers on (001)-oriented 0.7PbMg<sub>1/3</sub>Nb<sub>2/3</sub>O<sub>3</sub>-0.3PbTiO<sub>3</sub> (PMN-PT). The enhancement is coming from the fusion of magnetic skyrmions and electro resistivity tuned by strain simultaneously. The functionality of the strain-mediated RC system is successfully achieved via a sequential waveform classification task with the recognition rate of 99.3% for the last waveform, and a Mackey-Glass time series prediction task with normalized root mean square error (NRMSE) of 0.2 for a 20-step prediction. Our work lays the foundations for low-power neuromorphic computing systems with magneto-electro-ferroelastic tunability, representing a further step towards developing future strain-mediated spintronic applications.

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